AbstractOlfactory navigation in insects, for instance when males search for mates, is a navigational problem of a self-propelled agent with limited sensor capabilities in a scalar field (odor) convected and diffused by turbulent wind. There are numerous navigation strategies proposed to explain the navigation paths of insects to food (flowers) or mating partners (females). In a search for a mate, the males use airborne pheromone puffs in turbulent environments around trees and vegetation. It is difficult to compare the various strategies because of a lack of a single simulation framework that can change a single parameter in time and test all the strategies against a controlled environment. This work aims at closing this gap, suggesting an open source, freely accessible simulation framework, abbreviated MothPy. We implement the simulation framework using another open source package (“pompy”) that recreates a state-of-the-art puff-based odor plume model of Farrell et al. [1]. We add four different navigation strategies to the simulation framework based on and extending the previously published models [2, 3], and compare their performance with different wind and odor spread parameters. We test a sensitivity analysis of the navigation strategies to the plume meandering and to increased turbulence levels that are effectively expressed as the elevated puff spread rates. The simulations are compared statistically and provide an interesting view on the robustness and effectiveness of various strategies. This benchmarking-ready simulation framework could be useful for the biology-oriented, as well as engineering-oriented studies, assisting to deduce the evolutionary efficient strategies and improving self-propelled autonomous systems in complex environments.
Open source computational simulation for a moth-inspired navigation algorithm
